- 學位論文
利用搜尋法求解客服中心人員排班問題
Solving Call Center Agent Shift Scheduling Problem by Search Algorithms
摘要
顧客滿意度的高低對企業來說舉足輕重的影響，它對於一個企業的成功扮演著關鍵的角色。本篇論文探討一二十四小時客服中心之人員排班問題。為了要使顧客的需求達到最大的滿足，我們的目標是要找出一最佳排班表來使所缺乏的人力資源量為最少。 在本篇論文研究中，我們希望能同時考量到客服中心擁有變動需求、每位客服人員所擁有的技能不同且並非唯一、政府相關法規限制的這些現實因素並由啟發式演算法在合理的計算時間內求得一不錯的解。採用四種搜尋法(模擬退火法、塔布搜尋法、基因演算法、變動鄰近解搜尋法)來求解客服中心之人員排班問題。透過建構一線性規劃模型來針對每一個時間區段的技能需求進行人力資源配給使得短缺成本為最小。最後進行電腦模擬實驗來評估應用四種啟發式演算法的績效。結果顯示在本研究問題中，模擬退火法相較於其它方法表現較好。
並列摘要
A customer call center that provides services with high level of customer satisfaction is crucial to a successful modern company. This study solves the agent shift scheduling problem for a 24-hours call center. The objective of our problem is to minimize the shortage of man hour for customer demands of various skills. Considering time-varying demands, different skills, and various regulations, this study uses meta-heuristic algorithms to find near optimal solutions within a reasonable computation time. There are four algorithms (simulated annealing, tabu search, genetic algorithm, and variable neighborhood search) used to solve the combinatorial decision part of the agent scheduling problem. To compute the minimized shortage costs, each of the four algorithms uses a linear programming formulation to allocate man hours to the requirement of various skills. To compare the performance of these four algorithms, computational experiments are conducted. The results show that simulated annealing performs significantly better than the other algorithms in almost all the tested problems.